AI-102T00: Designing and Implementing a Microsoft Azure AI Solution
Designing and Implementing a Microsoft Azure AI
Certification AI-102T00: Designing and Implementing a Microsoft Azure AI Solution


- AI Fundamentals & Decision Support – Understand core AI concepts and solutions.
- Computer Vision & NLP – Work with image analysis, text processing, and facial recognition.
- Conversational AI & Bots – Develop intelligent chatbots and virtual assistants.
- Cognitive Services Integration – Implement Vision, Language, Speech, and decision support solutions.
- Hands-on Labs & Real-world Applications – Gain practical experience in deploying AI models.
- Security & Containerization – Manage AI solutions securely within Azure.

Fundamental Learnings
Training by Top Microsoft-Certified Trainers
1 Day of Live, Instructor-Led Sessions
Latest, Up-to-date Curriculum, Approved by Industry Experts
Access to a Digital Library of Learning Resources
Comprehensive Knowledge of Core Learnings
Blend of classroom sessions and hands-on training
Schedules
Prerequisites for this Courese
Prerequisites and Eligibility
- Familiarity with Azure fundamentals.
- Experience with C#, Python, or a similar programming language.
- Basic understanding of AI concepts and machine learning.

Things Included in the course learning
Course Curriculum
Module 1: – Introduction to AI and AI on Azure
• Introduction to AI
• Considerations for responsible AI
• Azure Machine Learning
• Introduction to azure ai services
• Azure AI services rest API and sdk
• Considerations of azure ai services security
• Monitor azure ai services
• Deploy azure ai services in containers
• Exercise: Get started with azure ai services
• Exercise: Manager azure ai service security
• Exercise: Monitor azure ai services
• Exercise: Use azure ai services container
Module 2: – Develop computer vision solutions with azure ai vision
• Azure AI Vision – Image Analysis
• Image analysis API and options
• Azure AI vision OCR
• Face detection, analysis and recognition
• Custom azure ai vision model for classification and object detection
• introduction to video indexer for video analysis
• Exercise: Explore features in Vision Studio
• Exercise: Analyze Images with Azure AI Vision
• Exercise: Read text in images
• Exercise: Detect and analyze faces
• Exercise: Classify Images with Azure AI Vision custom model
• Exercise: Analyze the video using video indexer
Module 3: – Develop natural language processing solutions
• Introduction to azure ai language service for language analysis
• Text translation using translator service
• Introduction to question and answering
• Creating a knowledge base
• Introduction to the language understanding
• Custom text classification
• Introduction to the speech service
• Introduction to speech synthesis markup language
• Translating speech to text
• Exercise: Analyze text
• Exercise: Translate text
• Exercise: Create a question and answering solution
• Exercise: Create a conversational language understanding app
• Exercise: Recognize and Synthesize Speech
Module 4: – Develop generative ai solutions with azure open AI service
• Introduction to generative ai
• Introduction to azure open-ai studio
• Various types of models in azure OpenAI
• Various Api's in azure OpenAI
• Testing models in azure OpenAI studio playground
• Integrating Azure OpenAI into your app
• Using the Azure OpenAI REST API: completion, chat completion
• Prompt engineering in azure OpenAI
• Implement Retrieval Augmented Generation (RAG) with Azure Open AI Service
• Exercise: Provision an Azure OpenAI resource in Azure
• Exercise: Get started with Azure OpenAI Service
• Exercise: Integrate Azure OpenAI into your app
• Exercise: Utilize prompt engineering in your app Exercise: Implement Retrieval Augmented Generation
(RAG) with Azure OpenAI Service
Module 5: – Creating the knowledge mining solution
• Introduction to the azure ai search
• Core Components of an AI Search Solution
• How an Enrichment Pipeline Works
• Introduction to Custom Skills
• What is a Knowledge Store?
• Implementing a Knowledge Store
• Exercise – Create an Azure Cognitive Search Solution
• Exercise – Create a Custom Skill for Azure AI Search
Module 6: – Develop solutions with Azure AI Document Intelligence
• Introduction to Document Intelligence Service
• Prebuilt models in document intelligence service
• Custom models in document intelligence service
• Exercise – Use prebuilt Document Intelligence models
• Exercise – Extract Data from Form
Things Included in the course learning
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What will I learn in this course
Output of this Course
- AI Fundamentals & Decision Support – Understand core AI concepts and solutions.
- Computer Vision & NLP – Work with image analysis, text processing, and facial recognition.
- Conversational AI & Bots – Develop intelligent chatbots and virtual assistants.
- Cognitive Services Integration – Implement Vision, Language, Speech, and decision support solutions.
- Hands-on Labs & Real-world Applications – Gain practical experience in deploying AI models.
- Security & Containerization – Manage AI solutions securely within Azure.
Who Should Enroll Now Azure AI Fundamentals Course
Who is this course for
- Software Engineers and Developers with an interest in AI
- AI and Machine Learning Engineers
- Data Scientists looking to apply AI in their models
- Cloud Solution Architects focusing on AI-based solutions
- IT Professionals aiming to expand their Azure skillset
- Technical Leads and Project Managers overseeing AI projects
- DevOps Engineers integrating AI into CI/CD pipelines
- Application Builders incorporating AI features into apps
- University Students and Researchers in computer science
- Professionals preparing for the Azure AI Engineer Associate certificat

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LevelIntermediate
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Duration32 hours
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Last UpdatedFebruary 1, 2025
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CertificateCertificate of completion